工程科学学报2017，Vol.39Issue(7)：981-987,7.DOI:10.13374/j.issn2095-9389.2017.07.002
基于最大池化稀疏编码的煤岩识别方法
A coal-rock recognition method based on max-pooling sparse coding
摘要
Abstract
Because of the lack of coal-rock methods, a novel coal-rock recognition method was proposed based on max-pooling sparse coding in order to explore new coal-rock image recognition methods and efficiently handle high-dimensional coal-rock image data.This method adds the pooling operation when extracting coal-rock image features and adopts the integrated classifier, which consists of multiple weak classifiers when classifying coal-rock images.The experimental results show that this feature-extraction method based on max-pooling sparse coding can simply and effectively express the characteristic information of coal-rock images, greatly enhance the distinguishability of coal-rock images, and achieve a high recognition rate.This method also has good recognition stability.The results obtained herein could provide a new idea and method for automatic coal-rock interface recognition.关键词
煤岩识别/图像处理/最大池化/稀疏编码/特征提取/集成分类Key words
coal-rock recognition/image processing/max-pooling/sparse coding/feature extraction/integrated classification分类
矿业与冶金引用本文复制引用
伍云霞,田一民..基于最大池化稀疏编码的煤岩识别方法[J].工程科学学报,2017,39(7):981-987,7.基金项目
国家重点研发计划资助项目(2016YFC0801800) （2016YFC0801800）
国家自然科学基金重点资助项目(51134024) （51134024）
